Sharif Digital Repository

In this work we study control independence in embedded processors. We classify control independent instructions to data dependent and data independent and measure each group's frequency and behavior. Moreover, we study how control independent instructions impact power dissipation and resource utilization. We also investigate control independent instructions' behavior for different processors and branch predictors. Our study shows that data independent instructions account for 34% of the control independent instructions in the applications studied here. We also show that control independent instructions account for upto 12% of the processor energy and 15.6%, 11.2% and 8.6% of the instructions... 

Job scheduling in MapReduce plays a vital role in Hadoop performance. In recent years, many researchers have presented job scheduler algorithms to improve Hadoop performance. Designing a job scheduler that minimizes job execution time with maximum resource utilization is not a straightforward task. The primary purpose of this paper is to investigate agents affecting job scheduler efficiency and present a novel classification for job schedulers based on these factors. We provide a comprehensive overview of existing job schedulers in each group, evaluating their approaches, their effects on Hadoop performance, and comparing their advantages and disadvantages. Finally, we provide... 

Adaptive routing algorithms help balancing the resource utilization in different parts of the network and hence, prevent a resource becoming the performance bottleneck while other resources are still under-utilized. In this paper, we present a novel approach, called Preemptive Waiting, which is applied to Odd-Even routing algorithm (PWOE). PWOE postpones the saturation traffic rate of NoC by 13.4% compared to OE, under synthetic traffic loads. © 2016 IEEE  

In cloud investment markets, consumers are looking for the lowest cost and a desirable fairness while providers are looking for strategies to achieve the highest possible profit and return. Most existing models for auction-based resource allocation in cloud environments only consider the overall profit increase and ignore the profit of each participant individually or the difference between the rich and the poor participants. This paper proposes a multi-dimensional fairness combinatorial double auction (MDFCDA) model which strikes a balance between the revenue and the fairness among participants. We solve a winner determination problem (WDP) through integer programming which incorporates the... 

Abstract Reducing the NoC power is critical for scaling up the number of nodes in future many-core systems. Most NoC designs adopt packet-switching to benefit from its high throughput and excellent scalability. These benefits, however, come at the price of the power consumption and latency overheads of routers. Circuit-switching, on the other hand, enjoys a significant reduction in power and latency of communication by directing data over pre-established circuits, but the relatively large circuit setup time and low resource utilization of this switching mechanism is often prohibitive. In this paper, we address one of the major problems of circuit-switching, i.e. the circuit setup time... 

We present and evaluate Deep Private-Feature Extractor (DPFE), a deep model which is trained and evaluated based on information theoretic constraints. Using the selective exchange of information between a user's device and a service provider, DPFE enables the user to prevent certain sensitive information from being shared with a service provider, while allowing them to extract approved information using their model. We introduce and utilize the log-rank privacy, a novel measure to assess the effectiveness of DPFE in removing sensitive information and compare different models based on their accuracy-privacy trade-off. We then implement and evaluate the performance of DPFE on smartphones to... 

In this paper, we consider the problem of overlay generation for video adaptation and streaming applications in a way to efficiently utilize the bandwidth and computing power of the participating peers. Therefore, the proposed architecture performs regular streaming functions as well as video adaptation functions, moving the video contents adaptation computation load away from dedicated media-streaming/adaptation servers to the participating peers. To verify the performance of our design, we followed an analytical approach based on 0-1 Integer Linear Programming method to model the system and to æakulate the optimum overlay. The performance of our scheme is evaluated by simulations.... 

Multi-application execution in Graphics Processing Units (GPUs), a promising way to utilize GPU resources, is still challenging. Some pieces of prior work (e.g. spatial multitasking) have limited opportunity to improve resource utilization, while others, e.g. simultaneous multi-kernel, provide fine-grained resource sharing at the price of unfair execution. This paper proposes a new multi-application paradigm for GPUs, called NURA, that provides high potential to improve resource utilization and ensure fairness and Quality-of-Service(QoS). The key idea is that each streaming multiprocessor (SM) executes the Cooperative Thread Arrays (CTAs) that belong to only one application (similar to... 

Multi-application execution in Graphics Processing Units (GPUs), a promising way to utilize GPU resources, is still challenging. Some pieces of prior work (e.g. spatial multitasking) have limited opportunity to improve resource utilization, while others, e.g. simultaneous multi-kernel, provide fine-grained resource sharing at the price of unfair execution. This paper proposes a new multi-application paradigm for GPUs, called NURA, that provides high potential to improve resource utilization and ensure fairness and Quality-of-Service(QoS). The key idea is that each streaming multiprocessor (SM) executes the Cooperative Thread Arrays (CTAs) that belong to only one application (similar to... 

An increasing trend for reducing cost, space, and weight leads to modern embedded systems that execute multiple tasks with different criticality levels on a common hardware platform while guaranteeing a safe operation. In such mixed-criticality (MC) systems, multiple worst case execution times (WCETs) are defined for each task, corresponding to the system operation mode to improve the MC system's timing behavior at runtime. Determining the appropriate WCETs for lower criticality (LC) modes is nontrivial. On the one hand, considering a very low WCET for tasks can improve the processor utilization by scheduling more tasks in that mode, on the other hand, using a larger WCET ensures that the... 

This paper presents a hybrid QR decomposition (QRD) design that reduces the number of computations and increases their execution parallelism by using a unique combination of Multi-dimensional Givens rotations, Householder transformations and conventional 2-D Givens rotations. A semi-pipelined semi-iterative architecture is presented for the QRD core, that uses innovative design ideas to develop 2-D, Householder 3-D and 4-D/2-D configurable CORDIC processors, such that they can perform the maximum possible number of vectoring and rotation operations within the given number of cycles, while minimizing gate count and maximizing the resource utilization. Test results for the 0.3 mm 2 QRD chip,... 

This paper presents a new negotiation model for designing Market- and Behavior-driven Negotiation Agents (MBDNAs) that address computational grid resource allocation problem. To determine the amount of concession for each trading cycle, the MBDNAs are guided by six factors: (1) number of negotiator's trading partners, (2) number of negotiator's competitors, (3) negotiator's time preference, (4) flexibility in negotiator's trading partner's proposal, (5) negotiator's proposal deviation from the average of its trading partners proposals, and (6) previous concession behavior of negotiator's trading partner. In our experiments, we compare grid resource consumer (GRC) of type MBDNAs (respectively... 

AQM router aims primarily to control the network congestion through marking/dropping packets which are used as congestion feedback in traffic sources to balance their flow rate. However, stabilizing queuing delay and maximizing link utilization have been considered as the main control objectives, especially in media dominated networks. Usually, most of the AQM algorithms are designed for a nominal operating point. However, time-varying nature of network parameters frequently violates their robustness bounds. In this paper, a self-tuning compensated PID controller is proposed to address the time-varying nature of network conditions caused by parameter variations and unresponsive connections.... 

On-chip interconnections play an important role in multi/many-processor systems-on-chip (MPSoCs). In order to achieve efficient optimization, each specific application must utilize a specific architecture, and consequently a specific interconnection network. For design space exploration and finding the best NoC solution for each specific application, a fast and flexible NoC simulator is necessary, especially for large design spaces. In this paper, we present an FPGA-based NoC co-simulator, which is able to be configured via software. In our proposed NoC simulator, entitled DuCNoC, we implement a Dual-Clock router micro-architecture, which demonstrates 75x-350x speed-up against BOOKSIM.... 

We present and evaluate Deep Private-Feature Extractor (DPFE), a deep model which is trained and evaluated based on information theoretic constraints. Using the selective exchange of information between a user's device and a service provider, DPFE enables the user to prevent certain sensitive information from being shared with a service provider, while allowing them to extract approved information using their model. We introduce and utilize the log-rank privacy, a novel measure to assess the effectiveness of DPFE in removing sensitive information and compare different models based on their accuracy-privacy trade-off. We then implement and evaluate the performance of DPFE on smartphones to... 

In this paper, we propose a packet-switched network-on-chip (NoC) architecture which can provide a number of low-power, low-latency virtual point-to-point connections for communication flows. The work aims to improve the power and performance metrics of packet-switched NoC architectures and benefits from the power and resource utilization advantages of NoCs and superior communication performance of point-to-point dedicated links. The virtual point-to-point connections are set up by bypassing the entire router pipeline stages of the intermediate nodes. This work addresses constructing the virtual point-to-point connections at run-time using a light-weight setup network. It involves monitoring... 

Although several analytical models have been proposed for wireless sensor networks (WSNs) with different capabilities, very few of them consider the effect of general service distribution as well as design constraints on network performance. This paper presents a new analytical model to compute message latency in a WSN with loop-free Bellman Ford routing strategy. The model considers limited buffer size for each node using M/G/1/k queuing system. Also, contention probability and resource utilization are suitably modeled. The results obtained from simulation experiments confirm that the model exhibits a high degree of accuracy for various network configurations. © 2009 IEEE  

To address sustainability challenges appeared in today's power grids, it is essential for emerging demand control paradigm to be adapted more to the lifestyle of the customers. In this paper, due to the ever-growing interconnectivity of the grids, a distributed Commodity Market (CM) framework is proposed in which intelligent agents embedded inside of customers want to maximize their preferred welfare through real-time demand of power from an energy market. Since there is not a comprehensive model for the grids, utilizing Reinforcement Learning (RL) proves that the global optimal performance is achieved in the Nash Equilibrium (NE) of the proposed framework. This solution not only maximizes... 

AQM router aims primarily to control the network congestion through marking/dropping packets which are used as congestion feedback in traffic sources to balance their flow rate. However, stabilizing queuing delay and maximizing link utilization have been considered as the main control objectives, especially in media dominated networks. Usually, most of the AQM algorithms are designed for a nominal operating point. However, time-varying nature of network parameters frequently violates their robustness bounds. In this paper, a self-tuning compensated PID controller is proposed to address the time-varying nature of network conditions caused by parameter variations and unresponsive connections.... 

Multi-application execution in Graphics Processing Units (GPUs), a promising way to utilize GPU resources, is still challenging. Some pieces of prior work (e.g., spatial multitasking) have limited opportunity to improve resource utilization, while other works, e.g., simultaneous multi-kernel, provide fine-grained resource sharing at the price of unfair execution. This paper proposes a new multi-application paradigm for GPUs, called NURA, that provides high potential to improve resource utilization and ensures fairness and Quality-of-Service (QoS). The key idea is that each streaming multiprocessor (SM) executes Cooperative Thread Arrays (CTAs) belong to only one application (similar to the...